Haystack
Open-source AI orchestration framework for production-ready RAG and agents
Overview
Haystack by deepset is an open-source AI orchestration framework for building context-engineered, production-ready LLM applications. It lets you design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems. With 25k+ GitHub stars and a vibrant community, Haystack provides a flexible component-based architecture that integrates with over 200+ model providers, vector databases, and document stores.
Requirements
Min vCPU
1
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
2
Rec RAM
4096 MB
Rec Disk
20 GB
Recommended VPS
Hostinger · KVM 2
2 vCPU · 8192 MB · 100 GB
Hostinger · KVM 2
2 vCPU · 8192 MB · 100 GB
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Affiliate disclosure
Docker Compose
# Generated by Run This Ai — docker-compose.yml
services:
haystack:
image: deepset/haystack:latest
restart: unless-stopped
ports:
- 8080:8080
volumes:
- ./data/haystack:/data
Related tools
LangChain
Build context-aware reasoning applications powered by LLMs
Supabase
Open-source Postgres platform for AI apps with vector search, realtime subscriptions & built-in dashboard
RedisStack
Redis with integrated modules for vector search, JSON, and search capabilities
Meilisearch
Lightning-fast search engine with AI-powered hybrid and vector search
PrivateGPT
Chat with your documents privately using LLMs — 100% local, no data leaks
Milvus
High-performance cloud-native vector database for scalable ANN search